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Reason? Sampling bias. Who are the players 6’5” and greater? And do they appear in both sets (aging)? You only have 10% of the sample, and so, much more likely for wild swings. Create 4 groups of 25% of the ballplayers, and I’d bet you get smooth results.
Pizza lays out the idea. As studes noted, we talked about this alot in the past.
What Brian suggests in the comments is the way I normally approach the problem, as the way Voros did it. Here are my aging patterns by these metrics.
I also echo Pizza’s position on where to put the HR. Sometimes I do it the way Pizza says it, and sometimes the way Voros says it. The fact of the matter is that you can construct two equally plausible scenarios.
There is an undeniable relationship between K, BB, and HR. There is also an undeniable relationship between HR and FB (and to a lesser extent LD). The only rigtht way to do it is to model this relationship. If for example you do it as Pizza proposes it, then you need to have an additional function on the HR/FB rate that includes the K and BB rate. If you do it as Voros proposes it, you need to include the FB rate to apply to the HR rate.
Rally looks at the relative strength of each league by looking at players that move league-to-league. But, instead of looking at the players in-season, or season-to-season, he looks at decade-to-decade.
I have some concerns, especially if age-wise, the movement is biased and there are no age adjustments. That’s why in-season works so well. That also means the sample size kills you, as Rally is noting. In any case, it’s an interesting way to look at it, especially if you can handle the potential age bias.
Courtesy of Patriot.
I don’t really have much to add. Patriot noted that he uses a 73% offensive replacement level, likening it to a .350 OW%. Using PythagenPat and 4.5 RPG per team, I get .364. No biggie. Just wanted to point out that he should probably be saying .360 not .350. However, what if you look at it as one replacement guy with 8 average guys? In this case, this team will win .486 games, making our replacement level -.014 wins per game (or more accurately per one-ninth of a game slice). Adjusted to a per game basis, that’s -.014 times 9 equals -.126, or a .374 win%.
That is, rather than presuming 9 replacement-level hitters with a team of average defense, we presume 1 replacement-level hitter, 8 average hitters, and average defense. That gives you a .486 win%. The marginal impact is .014, which you “annualize” by multiplying by 9. Kinda like ERA for relievers. Anyway, to get it to my replacement level, I’d use 74% or 75%. We’re pretty much in agreement here.
With starters, if we repeat this process, but presume 5.4 IP per replacement start, and the bullpen gives him average support, then Patriot’s 125% gives you a starter win% of .390. To make it .380, you’d want 1.27 or 1.28. So, 125% is perfectly fine.
For relievers, it’s the same process as hitters, if you presume 1 IP per replacement relief. You’d want 106% or 107% of league average.
Anyway, basic core agreement, with just a smidge of disagreement on the peripherals.
“I know, for myself, when the hockey season was over, I couldn’t wait to play baseball. I had no interest in playing ice hockey until September. Then you get a guy like Gordie Howe, he couldn’t skate enough. I don’t have the answer, other than I think it’s good for kids to participate in all sports.”
...
According to Mr. Gretzky, there is a neighbouring town close by his Los Angeles residence that he described as “a baseball factory.”
“But not one kid has ever made it to major-league baseball from there,” Mr. Gretzky said. “It’s a tremendous program; a lot of them get scholarships and play Division 1, but to actually play major-league baseball, not one. But everybody asks the same thing, ‘Do you think my son can make pro?’ The answer is, he’s 15, just enjoy it. Just let them have fun.”
Strength of schedule, using sample or true talent?
Best teams actually having the best record?
Stay tuned…
Who are better fielders today: 2B or 3B?
I’m looking at the Fans’ Scouting Report, and looking to see who fans are more impressed with on their team between second basemen and third basemen.
Here are the teams that the Fans highly prefer their 3B to their 2B, with the glove:
Let’s go back to my original chart:
+1.0 C
+0.5 SS/CF
+0.0 2B/3B
-0.5 LF/RF
-1.0 1B
More specifically, when we look at this chart, it asks “How does the average player at this position compare to Willie Bloomquist?”. If we consider WFB as the ideal average fielder, we see that the average SS and CF are a bit better than Willie, while the average corner OF are a bit worse, etc, etc. (If you don’t like the Willie comp, use someone else. Say Melvin Mora. He’s got average traits in the Fans Scouting Report across the board. He has close to a 0 UZR from 03-07. He started life as an OF and is now an IF. Whatever. Just choose one guy.)
That was based on players who play multiple positions. However, insofar as the IF is concerned, this excludes all LH throwers. That is, the comparison of that chart is to a righthanded WFB or Mora. However, what would the chart look like if we compare those players to a LEFTHANDED Mora?
In a recent thread, we have kind of settled down on around 40 plays, which is around 30 runs, or 3 wins, as the cost of putting a LH thrower in the infield (2b,ss,3b).
So, here is the above chart, but when compared to a lefthanded average fielder:
+3.5 SS
+3.0 2B/3B
+2.0 C
+0.5 CF
-0.5 LF/RF
-1.4 1B
All I did was add 3 wins to our IF, and I added 1.0 wins to the catcher. I moved the 1B downward by 0.4 wins (presuming a lefty is slightly more beneficial). The OF positions remained the same.
I’ll reset the above chart so that average is zero, so I will knock out 1.2 wins from everyone:
+2.3 SS
+1.8 2B/3B
+0.8 C
-0.7 CF
-1.7 LF/RF
-2.6 1B
So, that’s what the average fielder looks like when compared to a LH Mora.
From 2000-2007, 14.5% of the innings from nonpitchers were fielded by LH throwers. So, if we take 85.5% of the first chart, and 14.5% of this last chart, we get this:
ALL RH LH
1.0 1.0 0.8 C
0.8 0.5 2.3 SS
0.3 0.5 -0.7 CF
0.3 0.0 1.8 2B/3B
-0.7 -0.5 -1.7 LF/RF
-1.2 -1.0 -2.6 1B
If we try to make it a bit symmetrical, we get:
1.25 C
0.75 SS
0.25 CF/2B/3B
-.75 LF/RF
-1.25 1B
(I bumped the catcher a bit because I’ve probably been shortchanging them from the beginning. And I like symmetry. 
)
As you can see, this is identical to my original altered chart in the first linked thread. It conforms better to what we would think, while being able to arrive at the results in a somewhat logical manner.
The average of the three OF positions is -0.42 wins and the three IF positions is +0.42 wins.
This gap is 0.83 wins (compared to my original 0.33 wins). And it conforms more closely to what the offensive gap is between the two groups (around 1.2 wins).
So, what do we think?
Endy Chavez is one of our generations best fielding outfielders. He also happens to throw lefthanded. Frank Thomas is one of our generations worst fielding infielders. He’s a righty. If you were to put each of them at shortstop, who would fare better? Whatever extra time it takes for Endy to set himself to throw is less than whatever time it takes for Thomas to get to the ball (if he can even manage to get to the ball in the first place). But, this one is easy.
The question is how much does being a lefty disadvantage Endy? How many plays does it cost him? If the difference between Adam Everett (pre-injury) and Frank Thomas playing shortstop is say an extra 100 plays made, and an average shortstop and Frank Thomas is 70 plays made, where does the lefthanded Endy Chavez fall in this continuum? Would he fare better or worse than putting Rickie Weeks at SS? Better or worse than putting Ryan Braun there? Take the worst-fielding 2B or 3B in baseball, and put him at shortstop. Say this player makes 40 plays more than Frank Thomas at shortstop. Is Endy better or worse than that guy?
The question therefore is: how many plays do you think being lefthanded costs an otherwise fantastic fielder? (My question is NOT whether a manager will ever do it.)
See, we can come to a reasonable agreement as to how many runs speed is worth, anticipation is worth, arm strength, accuracy, catching a ball, etc. I’m wondering how well can we agree on the throwing hand of an infielder.
Bonus: In the early days of baseball, I suppose when Frank Thomas-likes were more than an option, they did resort to lefthanded shortstops. Here are 42 of the 43:
Cool interview. Great quote right here:
Coach Bagonzi: If a young pitcher doesn’t start to develop a curveball early in his career (age 15-plus), I don’t think he will ever have a good one. So, I agree with your contact who says that if he can’t spin it by age 19, forget it, and I think that is why there are so many sliders (the “devil’s pitch”) - it’s the quick fix.
In fact, I talked with the pitching coach of the Rangers a few years back when they [still] trained in Port Charlotte, Florida, and asked him why there were so many sliders and so few curveballs among the Rangers’ pitchers, and he quite emphatically stated that the young pitchers’ “window of opportunity” was small and narrow, and the slider could be learned faster, and this became the “fix.”
That is why before a young pitcher signs, it would be good if he had a curveball - a good, down-breaking 12-to-6 curveball with crispness thrown for strikes. This enhances the fastball and its effect multifold. Pitching up and down trajectory-wise is a devastating event, even for the good hitter; the trouble is that few pitchers do it well. Those that do are generally winners and high-strikeout guys. [Nolan] Ryan had a good curveball, and this made him electrifying.
Curveballs are less stressful on the arm than sliders because of the deceleration of the arm on release. However, one has to be aware of losing arm speed on their fastball if too many curveballs are thrown. A curveball should precede a slider in the learning business.
Why is it we only get good stuff like this from the mainstream media and not blogs?
{Dripping with sarcasm.}
Yesterday, Batters Box highlighted the difference in opposition quality (both offense and pitching) faced by Cliff Lee and Roy Halladay, as did Joe Sheehan.
Since MGL includes strength of schedule and park in his adjustments, perhaps we can prevail upon him to comment on this wide disparity.
Also: In the Batter’s Box post, they show the ERA+ (note: if you have Firefox, it’s off the page, and you wouldn’t even know it’s there. Keep clicking CTRL-, that’s Control Key and Minus sign at the same time, until you see it). Guess how the average ERA+ was calculated? That’s right, the wrong way. As readers here know, since ERA+ flipped the denominator, in order to calculate the correct average ERA+, you need to do: 1 / average (1/ERA+). Indeed, once you do that, the opposition ERA+ of Hallday goes from 104 to 96! Cliff Lee goes from 96.5 to 89.
Sean Forman: please, stop the insanity, and stop making ERA+ a “bigger is better”. You’ve got alot of really smart people making simple math mistakes.
Great job by Clay in going through a list of the best minor-leaguers over 30. He concludes that the best nonpitchers would score 3.7 runs per game, and the pitchers would allow 5.0 runs per game (and when you include the slightly below average fielding, all the way up to 5.2 runs per game). That works out to a .350 win%.
The best team of players who have no hope of playing in MLB would win 35% of the time. Most analysts have argued that the number is somewhere around the 27% to 35% level. Clay’s number here is a bit on the high-end, but certainly believable. I would not be surprised that the players have a selection bias and probably not enough regression, and so, we can see that perhaps they would really score 3.5 runs per game and allow 5.5 runs per game. That would imply a .300 win%.
Clay’s WARP however presumes a 25-win level for a replacement level team, or a .154 win%. I hope that Clay may have convinced himself that WARP needs to rethink its position about replacement level, and join the rest of us. A guy who puts in as much effort and thought in doing the work he does to distribute the work to as many people as he does deserves our respect. There is a sizable community that takes this WARP stuff seriously, and hopefully Clay can recognize that.
UPDATE: For those who want more of my takedown of WARP, you can read about it here.
UPDATE2: And here.
As AsrosFan is telling us:
I was just glancing at Andrew Dolphin’s ratings of MLB teams. I decided to go with the Predictive ranking.
Predictive Both schedule strength and rating vs. schedule strength are determined considering both the wins and losses and the score differentials. This rating contains none of the biases in the standard rating, but does weight recent games slightly more than past games since those are a better indication of the team’s current strength. This rating is the best of the first three for seeing how good teams are, and thus is the best for predicting future results.I could have used Improved RPI, but I wanted one that included run differential. Here are the rankings of all 30 teams: http://www.dolphinsim.com/ratings/mlb/index_pred.html
The first thing we notice is that the AL is ranked as having 10 out the top 11 teams. Mr. Dolphin’s analysis shows the AL as being much stronger, and thus teams with worse records than NL teams can actually be better due to strength of schedule. Indeed, looking at it from the expected losses standpoint, which Mr. Dolphin says “can be used to rank schedules”, the top 14 SOS are in the AL, meaning all the AL teams. And it’s not really close.
That would be astonishing enough, but this is what really caught my eye. Down further on the page, the rankings are split up by division. If we scroll to the AL East, we find these rankings: Boston: 1 Tampa Bay: 3 Toronto: 7 New York Yankees: 9 Baltimore: 10 . All five teams in the AL East are ranked in the top 10, that is, the top third of baseball. Baltimore, which at the time of the latest update, had a 61-66 record and RS/RA of 653/653, is ranked two spots ahead of Milwaukee, which had a 75-55 record and a RS/RA of 616/555.
To which I responded to the above and other questions in that thread:
Stumbling on this cool article on the platoon advantage of same-handed shooters and goalies (RH shooters prefer to play against goalies who have a glove on the RH, meaning that the stick and glove are on opposite sides, just like a RH pitcher is on opposite side of a LH hitter), there was a comment about how a disproportionate number of Canadians are LHH in baseball. It certainly makes sense, since the number of LH shooters in hockey is disproportionately large, and a LH shooter in hockey will become mostly a LH hitter in baseball. Here’s more on the subject.
Well-written article:
We all know that the map of Alberta and the territory of Alberta are two different things. The map might show that a road is straight, but when you head out to that road, you actually find that it curves here and there, that the territory itself is different than the map. So the map is not the territory, and it never is, and it never can be. When it comes to hockey, the map is the statistics we use to try to describe the performance of a player. The territory is the player’s performance itself. The map and the territory are two different things here as well. For instance, the statistical map might say that Shawn Horcoff was +3 on the night, but really he had a terrible game. Horcoff had little to do with any of the three goals scored when he was on the ice, and on one goal against his team, after making a terrible play, he left the ice before the goal was scored, so the minus mark went to some other player, not him. When you hear then, that Horcoff played great because he was +3 and he faced strong opponents, and that’s all you know about the matter, it’s important to realize that number has great limitations in describing the performance.
There are easy ways to handle plus/minus in hockey, and that’s the With Or Without You (WOWY) method. 82games.com does that for basketball. While the above author is correct that plus/minus has its flaws (giving a plus to someone who doesn’t deserve it, etc), that doesn’t matter. You can take say Albert Pujols and Benjie Molina, and then, randomly give each player 200 PA of a mean of .340 OBP (that is, let a random number generator, with mean = .340, and 1 SD = .030, create a number, then multiply that by 200), and add that to his totals. Guess what? Pujols will still have a higher OBP than Molina. Once in a blue moon Molina might end up with a higher OBP than Pujols because he lucked into a .600 OBP in 200 PA while Pujols lucked into a .100 OBP in 200 PA. But, the underlying basis of OBP (and plus/minus) still holds. The signal is still there, but now you have more noise to sift through.
Anyway, enjoyable read.
The ever-resourceful Ubi tells us:
From 2002 to 2005 there were 257 games played by teams in contention against teams out of it*. The contending team won 170 of those games for a .661 winning %. The contending teams record before the trial period was .553 and the out of it teas winning % was .394. Now then if I did Log5 correctly we should expect the contending team to win 65.5% of the time so according to Log5 contending teams over a 4 year period won 2 more games then expected.
*: Contending teams were defined as teams that were within 5 games of the division lead or wild card provided that they were over .500. Also division leaders or wild card teams that had big leads were not counted as contending teams. The out of it teams were the bottom dwelling teams of each league. The winnning percentages provided were based on standings at the end of play on Aug 31.
So, the idea that the contenders have it better against non-contenders because non-contenders are putting out “trial” lineups is almost certainly not true. Even if they are trial lineups, those trial lineups might have been the better option to begin with!
What is it about the male mindset that obligates power over cunning? There are literally thousands of minor league, college and high school pitchers who think they can make it to MLB. Of all pitchers born between 1968 and 1977 (that’s 10 years), there have been a little over one thousand guys to pitch in MLB. That’s about 100 pitchers born every year. And yet, millions of parents and thousands of kids think they are part of the elite 100.
If you want to distinguish yourself, why not throw a knuckler or throw sidearm. Really. And why don’t MLB teams actively create a “sidearm” training program, selecting 10 low-prospect pitchers every year for their sidearm program. That must have a better ROI shouldn’t it?
Adding two teams will do nothing that you will notice, that’s for sure. If you have 750 players in the league, adding the 751st to 800th best player will not affect anything you can notice. Pretend that the average player has “4 units of talent”. So that the average team has “100 units of talent”. With 750 players in the league, you have “3000 units of talent”. You add in 50 more players into the league each of which has 1 unit of talent. Now you have 3050 units of talent, but spread over 32 teams. The average team will now have 95 units of talent. You are not really going to notice. Not to mention that the number of US-born players playing in MLB since 1969 (24 teams) has not changed! All the extra players are coming from abroad. And they are holding their own. So, in reality, adding 2 teams really means adding 50 more foreign players (Japan has lots of players I hear). I’ll guarantee that if ever Japan/MLB can have a better transfer deal, you will get expansion in MLB.
Anyway, Maury talks about expansion, and I respond:
And I think they would be much better off if they didn’t try. Now, I am not saying that they are clueless because they don’t know the right answer. I am saying they are clueless because NO ONE knows the right answer and they think they do. That is just as bad, if not worse.
For example, this article:
http://www.nctimes.com/articles/2008/07/27/sports/padres/ze34b3eea7c83c1378825748d00575e7d.txt
goes on and on about because Petco is a big park you need pitching and defense. Alderson and Towers, two supposedly smart guys, say that over and over. I can’t for the life of me imagine why you need more good pitching in a pitchers park than in a hitters park. It is one of those stupid things that at a quick glance seems to make sense, but if you actually think about it for more than a minute with no pre-conceived notions, you have to shake your head and think, “Why would that be. That makes no sense.” Aren’t GM’s supposed to actually think about things for more than a second or two, or even talk to people who are smarter than they are?
The other thing that EVERYONE thinks is that you need speedy and good players on defense in a large park. In the article they even talk about Greene’s good defense in the same breath, as if Petco had a larger INFIELD than other parks!
Anyway, I am telling you again, that I looked hard and long at the notion of speedier or better outfielders being more valuable in larger parks than in smaller ones, and I absolutely, without doubt, can find NO evidence that this is the case. None, whatsoever. If it is true, like clutch hitting, it ain’t that big a thang. I really wish that EVERYONE would stop assuming that this is true.
In the same article above, someone stated that you want fly ball pitchers and you don’t want home run hitters in a big park. That also SEEMS to make sense. Except for the fact that again, there is no evidence that that is true. In fact, the reverse might be true. Since a park’s HR park factor is at least partially additive, you may benefit from having a HIGH home run hitter than a LOW home run hitter when your home park has a low HR park factor. Or at least it won’t matter.
There was even a quote from a guy in the article that suggested what they need are hitters who can hit line drives! As if in other parks, you want hitters who hit pop-ups and ground balls!
Basically, it is REALLY hard to figure out what kind of players are suited to the various parks. It is one of those things that sabermetrics has not “answered” yet. Yet, these idiots who run the teams try and try and in the process screw up their team.
I think they would be just a little better off if they just put together a good team, period, and didn’t worry about their park, especially considering that they have to play half their games on the road anyway.
As far as the Padres go, I would have to say that 95% of their “problem” this year has been bad luck, even though it looks like they have an awful team. If they think otherwise, they are going to screw up their team even more.
This is really SABR 101 stuff, so most of you will not care at all about this, but in case some newbies are around, I respond to Geoff Baker who says:
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